Salesforce AI Integration Architect ID68517

AgileEngine•Los Angeles, CA

1d•Remote

About The Position

We are looking for a Salesforce AI Integration Architect to design and build enterprise integrations between internal AI platforms, enterprise systems, and Salesforce Agentforce environments, enabling autonomous AI workflows at scale. You will architect distributed systems and multi-step agentic AI orchestration patterns, develop Salesforce-native integrations, and establish governance, security, and trust frameworks for AI-enabled enterprise solutions. The role requires deep expertise in Salesforce customization, AI/LLM orchestration, enterprise integrations, and scalable distributed system design.

Requirements

6+ years of experience designing enterprise integrations and distributed system architectures;
Hands-on experience integrating systems with Salesforce;
Deep expertise with Apex Methods, Advanced Salesforce Flows, Custom Prompt Templates, Salesforce APIs, and connectors;
Strong experience with REST APIs;
Solid understanding of AI/LLM concepts including Prompt Engineering, Context Management, Token Optimization, Multi-step AI Workflows, Agent Orchestration, and Semantic Routing Systems;
Experience designing scalable and secure distributed systems;
Strong understanding of authentication, security, trust boundaries, and data governance;
Experience documenting architecture decisions, trade-offs, and technical strategy;
Excellent collaboration and communication skills across engineering, platform, data, and security organizations;
Upper-intermediate English level.

Nice To Haves

Experience with gRPC;
Experience with Event-Driven Architectures;
Experience with enterprise synchronization patterns;
Experience with Model Context Protocol (MCP);
Experience with Agent-to-Agent (A2A) integrations;
Experience with MuleSoft or enterprise middleware platforms;
Familiarity with Salesforce Agentforce;
Experience building or managing autonomous AI agents or micro-agent ecosystems;
Experience with semantic tool discovery or AI-native integrations;
Knowledge of Salesforce Bulk APIs and Salesforce Connect;
Experience operating within large-scale enterprise AI environments.

Responsibilities

Architect end-to-end integrations between internal AI platforms, enterprise data systems, and Salesforce Agentforce environments;
Design scalable, secure, and resilient distributed system architectures supporting autonomous AI workflows;
Design and optimize modular agentic AI systems, avoiding monolithic reasoning architectures through specialized micro-agent delegation;
Build orchestration patterns for multi-step AI workflows, autonomous routing systems, and semantic tool execution;
Apply best practices around Prompt Engineering, Context Management, Token Conservation, and LLM Orchestration;
Develop and enhance integrations using Salesforce Flows, Invocable Apex Methods, APIs, connectors, and custom prompt templates;
Enable complex backend processes to be exposed as intelligent agentic tools within Salesforce ecosystems;
Collaborate with cross-functional teams to maintain unified API contracts and semantic consistency across enterprise systems;
Author comprehensive Architectural Decision Records (ADRs) documenting technical trade-offs, constraints, and High-Level Requirements (HLRs);
Evaluate and select optimal integration patterns including Traditional APIs, Model Context Protocol (MCP), and Agent-to-Agent (A2A) communication models;
Balance performance, latency, scalability, reasoning overhead, and data sensitivity considerations in architectural decisions;
Establish authentication boundaries, trust layers, and governance guardrails for AI-enabled enterprise systems;
Ensure compliance with enterprise security standards, data governance policies, and secure data exposure practices;
Partner with security and platform teams to maintain reliable and trustworthy autonomous agent execution.